首页|New Robotics Findings from Shanghai Jiao Tong University Described (High-precisi on Dynamic Control of Soft Robots With the Physics-learning Hybrid Modeling Appr oach)
New Robotics Findings from Shanghai Jiao Tong University Described (High-precisi on Dynamic Control of Soft Robots With the Physics-learning Hybrid Modeling Appr oach)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Fresh data on Robotics are presented i n a new report. According to news reportingoriginating from Shanghai, People’s Republic of China, by NewsRx correspondents, research stated, “Thecontinuum def ormation and nonlinear mechanical behaviors of soft materials make it challengin g todevelop an accurate and computationally efficient dynamic model for soft ro bots intended for real-time control purposes. In this article, we present a phys ics-learning hybrid modeling approach based on absolutenodal coordinate formula tion (ANCF) and the multilayer neural network (MLNN), achieving both real-times imulation and high-precision dynamic control for a class of soft parallel robots .”
ShanghaiPeople’s Republic of ChinaAs iaEmerging TechnologiesMachine LearningNano-robotRobotRoboticsShangh ai Jiao Tong University
NETL
NSTL
